• Qi, J., Uhlmann, Y., Schullerus, G. (2024). Intelligent Condition Monitoring for Mechanical Systems Using AI: A case study on Roller Chain System. In: Bosch Spring School on AI in Industry, Reutlingen, Germany, 06 March, 2024 - 07 March 2024.
• Qi, J., Zhu, R., Liu, C., Ricardo Mauricio, A., Gryllias, K. with Gryllias, K. (corresp. author) (2024). Anomaly detection and multi-step estimation based remaining useful life prediction for rolling element bearings. Mechanical Systems And Signal Processing, 206, Art.No. 110910. doi: 10.1016/j.ymssp.2023.110910
• Gryllias, K., Qi, J., Ricardo Mauricio, A., Liu, C. (2023). Condition Monitoring of Wind Turbine Drivetrain Bearings. Journal Of Engineering For Gas Turbines And Power-Transactions Of The Asme, Art.No. GTP-22-1001, 1-10. doi: 10.1115/1.4064366
• Qi, J., Gryllias, K., Ricardo Mauricio, A. (2022). Estimation of Remaining Useful Life of rolling element bearings based on state estimation techniques. Presented at the Flanders Make 2022 Conference on Machines, Vehicles and Production Technology, Ghent, 30 Mar 2022-30 Mar 2022.
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• Andre, H., Leclere, Q., Anastasio, D., Benaicha, Y., Billon, K., Birem, M., Bonnardot, F., Chin, Z.Y., Combet, F., Daems, P.J., Daga, A.P., De Geest, R., Elyousfi, B., Griffaton, J., Gryllias, K., Hawwari, Y., Helsen, J., Lacaze, F., Laroche, L., Li, X., Liu, C., Mauricio, A., Melot, A., Ompusunggu, A., Paillot, G., Passos, S., Peeters, C., Perez, M., Qi, J., Sierra-Alonso, E.F., Smith, W.A., Thomas, X. (2021). Using a smartphone camera to analyse rotating and vibrating systems: Feedback on the SURVISHNO 2019 contest. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 154, Art.No. ARTN 107553. doi: 10.1016/j.ymssp.2020.107553
• Qi, J., Ricardo Mauricio, A.M., Gryllias, K. (2021). Comparison of Blind Diagnostic Indicators for Condition Monitoring of Wind Turbine Gearbox Bearings. Journal Of Engineering For Gas Turbines And Power-Transactions Of The Asme, 7, Art.No. GTP-20-1604. doi: 10.1115/1.4049797
• Qi, J., Gryllias, K., Ricardo Mauricio, A. (2021). Estimation of Remaining Useful Life of rolling element bearings based on state estimation techniques. Presented at the Flanders Make Scientific Conference, Online/virtual, 04 Feb 2021-04 Feb 2021.
• Ricardo Mauricio, A.M., Qi, J., Smith, W., Sarazin, M., Randall, R., Janssens, K., Gryllias, K. (2020). Bearing diagnostics under strong electromagnetic interference based on Integrated Spectral Coherence. Mechanical Systems and Signal Processing, 140, Art.No. 106673. doi: 10.1016/j.ymssp.2020.106673
• Ricardo Mauricio, A.M., Qi, J., Zhou, L., Wang, W., Mba, D., Gryllias, K. (2019). Perspectives on Health and Usage Monitoring Systems (HUMS) of helicopters. Journal Of Engineering For Gas Turbines And Power-Transactions Of The Asme, 314, Art.No. 02008. doi: 10.1051/matecconf/202031402008
• Ricardo Mauricio, A.M., Qi, J., Gryllias, K. with Gryllias, K. (corresp. author) (2018). Vibration based condition monitoring of wind turbine gearboxes based on cyclostationary analysis. Journal of Engineering for Gas Turbines and Power, 141 (3), Art.No. 031026. doi: 10.1115/1.4041114
• Ricardo Mauricio, A.M., Qi, J., Gryllias, K. with Gryllias, K. (corresp. author) (2018). Vibration based condition monitoring of wind turbine gearboxes based on cyclostationary analysis. Journal of Engineering for Gas Turbines and Power, 141 (3), Art.No. 031026. doi: 10.1115/1.4041114
• Qi, J., Gryllias, K., Ricardo Mauricio, A. (2021). Multiple-Model Estimation-based Prognostics for Rotating Machinery. In: Proceedings of the European Conference of the PHM Society 2021: vol. 6 (1), (317-327). Presented at the 6th European Conference of the PHM Society, Virtual event, 28 Jun 2021-02 Jul 2021. ISBN: 978-1-936263-34-9. doi: 10.36001/phme.2021.v6i1.2956
• Liu, C., Ricardo Mauricio, A., Qi, J., Peng, D., Gryllias, K. (2020). Domain Adaptation Digital Twin for Rolling Element Bearing Prognostics. In: Online Proceedings of PHM2020, (1-10). Presented at the Annual Conference of the PHM Society 2020, Nashville, Tennessee, USA. doi: 10.36001/phmconf.2020.v12i1.1294
• Qi, J., Ricardo Mauricio, A., Gryllias, K. (2020). Prognostics of the Rotating Machinery Relying on the Multi-Steps Estimation Approach. In: Proceedings Of International Conference On Noise And Vibration Engineering (ISMA2020) / International Conference On Uncertainty In Structural Dynamics (USD2020), (713-728). Presented at the International Conference on Noise and Vibration Engineering (ISMA) / International Conference on Uncertainty in Structural Dynamics (USD), Leuven, Belgium, 07 Sep 2020-09 Sep 2020.
• Gryllias, K., Qi, J., Ricardo Mauricio, A.M., Liu, C. (2019). CONDITION MONITORING OF WIND TURBINE DRIVETRAIN BEARINGS. In: Proceedings of the ASME 2019 2nd International Offshore Wind Technical Conference IOWTC 2019. Presented at the 2nd International Offshore Wind Technical Conference IOWTC, St. Julian's, Malta. ISBN: 978-0-7918-5935-3. doi: 10.1115/IOWTC2019-7603
• Qi, J., Ricardo Mauricio, A.M., Gryllias, K. (2019). Prognostics of Rolling Element Bearings based on Entropy indicators and Particle Filtering. In: BOOK OF PROCEEDINGS SURVISHNO 2019. Presented at the Survishno 2019, Lyon, France, 08 Jul 2019-10 Jul 2019.
• Qi, J., Ricardo Mauricio, A.M., Gryllias, K. (2019). Prognostics of Rolling Element Bearings based on Entropy indicators and Particle Filtering. In: BOOK OF PROCEEDINGS SURVISHNO 2019. Presented at the Survishno 2019, Lyon, France, 08 Jul 2019-10 Jul 2019. 
• Qi, J., Ricardo Mauricio, A., Sarrazin, M., Janssens, K., Gryllias, K. (2018). Enhanced Particle Filter and Cyclic Spectral Coherence based Prognostics of Rolling Element Bearing. In: VOL 4 NO 1 (2018): Proceedings of the European Conference of the PHM Society. Presented at the Fourth European Conference of the PHM Society - PHME18, Utrecht, The Netherlands, 03 Jul 2018-06 Jul 2018.
• Ricardo Mauricio, A., Wade, S., Qi, J., Randall, R., Gryllias, K. (2018). Cyclo-non-stationary based bearing diagnostics of planetary gearboxes. In: Proceedings of the 6th International Conference on Condition Monitoring of Machinery in Non-stationary Operations: vol. 15, (343-352). Presented at the CMMNO2018 International Conference on Condition Monitoring of Machinery in Non-stationary Operations, Santader, Spain, 20 Jun 2018-22 Jun 2018. ISBN: 978-3-030-11220-2. doi: 10.1007/978-3-030-11220-2_35
• Qi, J., Ricardo Mauricio, A., Sarrazin, M., Janssens, K., Gryllias, K. (2018). Remaining Useful Life Prediction of Rolling Element Bearings based on Unscented Kalman Filter. In: Proceedings of the 6th International Conference on Condition Monitoring of Machinery in Non-stationary Operations: vol. 15, (Paper No. 39), (111-121). Presented at the CMMNO2018 International Conference on Condition Monitoring of machinery in Non-stationary Operations, Santander, Spain, 20 Jun 2018-22 Jun 2018. ISBN: 978-3-030-11220-2.
• Ricardo Mauricio, A., Qi, J., Sarrazin, M., Janssens, K., Smith, W., Randall, R., Gryllias, K. (2018). Cyclostationary-based bearing diagnostics under electromagnetic interference. In: 25th International Congress on Sound and Vibration 2018, ICSV 2018: Hiroshima Calling: vol. 5, (2860-2867). Presented at the 25th International Congress on Sound and Vibration 2018, ICSV 2018: Hiroshima Calling, Hiroshima, Japan, 08 Jul 2018-12 Jul 2018. ISBN: 9781510868458.
• Ricardo Mauricio, A., Qi, J., Gryllias, K. (2018). Vibration based condition monitoring of wind turbine gearboxes based on cyclostationary analysis. In: Proceedings of the ASME Turbo Expo: vol. 9, (Paper No. ARTN V009T48A017). Presented at the ASME Turbo Expo 2018: Turbomachinery Technical Conference and Exposition, Oslo, Norway, 11 Jun 2018-15 Jun 2018. ISBN: 9780791851180. doi: 10.1115/GT2018-76993
• Ricardo Mauricio, A.M., Gryllias, K., Qi, J. (2018). Advanced cyclostationary-based analysis for condition monitoring of complex systems. In: European Signal Processing Conference, (390-394). Presented at the 26th European Signal Processing Conference (EUSIPCO), Rome, Italy, 03 Sep 2018-07 Sep 2018. ISBN: 978-90-827970-1-5.
• Gryllias, K., Qi, J., Ricardo Mauricio, A., Vandenbrande, P-J. (2017). A semi-supervised SVDD-based fault detection method for rolling element bearings. (Paper No. 156). Presented at the World Congress on Condition Monitoring, ILEC Conference Centre, London, UK, 13 Jun 2017-16 Jun 2017

• Seit 2023: Wissenschaftlicher Mitarbeiter am Reutlingen Research Institute, Reutlingen, Deutschland
• 2017-2023: Wissenschaftlicher Mitarbeiter am LMSD, Department of Mechanical Engineering, KU Leuven, Leuven, Belgium
• 2015-2016: Bosch Rexroth, Lohr am Main, Deutschland
• 2013-2016: Master of Science Mechatronik, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Deutschland
• 2008-2012: Bachelor of Science Mechatronik, Shanghai Maritime University, China

Junyu has authored more than 20 papers published in reputable journals and conferences such as Mechanical System and Signal Processing, Journal Of Engineering For Gas Turbines And Power: Transactions Of The ASME, International Conference on Condition Monitoring of Machinery in Non-Stationary Operation (CMMNO), ASME Turbomachinery Technical Conference & Exposition (Turbo Expo), International Offshore Wind Technical Conference (IOWTC), European Conference of the PHM Society (PHME), International Conference on Noise and Vibration Engineering (ISMA), Conferences Surveillance-Vibration Shocks and Noise-Experimental Vibration Analysis (SURVISHNO), International Congress on Sound and Vibration (ICSV), European Signal Processing Conference (EUSIPCO), World Congress on Condition Monitoring (WCCM), among others. Moreover, he actively contributes to the academic community by serving as a reviewer for several esteemed journals including Mechanical System and Signal Processing, Reliability Engineering and System Safety, The IEEE/ASME Transactions on Mechatronics, Scientific Reports, Energy Reports, Multiscale and Multidisciplinary Modeling, Experiments and Design, Ain Shams Engineering Journal, Engineering Failure Analysis, and more. In 2020, he was honored with the Best Paper Award by the American Society of Mechanical Engineers for his outstanding research on the Fault Detection of Wind Turbine Gearboxes.

• Condition Monitoring und Predictive Maintenance
• Daten Analyse, z.B. Entwicklung im Zeitbereich, Frequenzbereich, und Zeit-Frequenz Bereich
• KI, z.B. Anomalieerkennung und restliche Lebensdauer vorhersagen